Integrating Fuzzy Logic Technique in Case-Based Reasoning for Improving the Inspection Quality of Software Requirements Specifications

2020 ◽  
pp. 503-513 ◽  
Author(s):  
Salama A. Mostafa ◽  
Saraswathy Shamini Gunasekaran ◽  
Shihab Hamad Khaleefah
Keyword(s):  
Fuzzy Logic ◽  
Software Requirements ◽  
Case Based Reasoning ◽  
Requirements Specifications ◽  
Fuzzy Logic Technique ◽  
Case Based

A Fuzzy Case-Based Reasoning Model for Software Requirements Specifications Quality Assessment

2019 ◽  
Vol 9 (6) ◽  
pp. 2134
Author(s):  
Salama A. Mostafa ◽  
Saraswathy Shamini Gunasekaran ◽  
Shihab Hamad Khaleefah ◽  
Aida Mustapha ◽  
Mohammed Ahmed Jubair ◽  
...  
Keyword(s):  
Quality Assessment ◽  
Software Requirements ◽  
Case Based Reasoning ◽  
Requirements Specifications ◽  
Case Based

Software Requirements Risk and Maintainability

2005 ◽  
pp. 2562-2566
Author(s):  
Norman F. Schneidewind
Keyword(s):  
Risk Factors ◽  
Life Cycle ◽  
Software Metrics ◽  
Space Shuttle ◽  
Software Requirements ◽  
Requirements Specifications ◽  
Requirements Change ◽  
Code Metrics ◽  
Change Requests

In order to continue to make progress in software measurement, as it pertains to reliability and maintainability, there must be a shift in emphasis from design and code metrics to metrics that characterize the risk of making requirements changes. By doing so, the quality of delivered software can be improved because defects related to problems in requirements specifications will be identified early in the life cycle. An approach is described for identifying requirements change risk factors as predictors of reliability and maintainability problems. This approach can be generalized to other applications with numerical results that would vary according to application. An example is provided that consists of 24 space shuttle change requests, 19 risk factors, and the associated failures and software metrics.

Soft case-based reasoning

2005 ◽  
Vol 20 (3) ◽  
pp. 267-269 ◽  
Author(s):  
WILLIAM CHEETHAM ◽  
SIMON SHIU ◽  
ROSINA O. WEBER
Keyword(s):  
Neural Network ◽  
Fuzzy Logic ◽  
Soft Computing ◽  
Network Theory ◽  
Probabilistic Reasoning ◽  
Case Based Reasoning ◽  
Case Representation ◽  
Soft Computing Techniques ◽  
Neural Network Theory ◽  
Case Based

The aim of this commentary is to discuss the contribution of soft computing—a consortium of fuzzy logic, neural network theory, evolutionary computing, and probabilistic reasoning—to the development of case-based reasoning (CBR) systems. We will describe how soft computing has been used in case representation, retrieval, adaptation, reuse, and case-base maintenance, and then present a brief summary of six CBR applications that use soft computing techniques.

Harmonic Reduction in Grid Connected Wind Energy System with Dynamic Voltage Restorer Using Fuzzy Logic Technique

2014 ◽  
Vol 626 ◽  
pp. 197-201
Author(s):  
B. Ashok Kumar ◽  
N. Kamaraj ◽  
C.K. Subasri
Keyword(s):  
Fuzzy Logic ◽  
Wind Energy ◽  
Power Quality ◽  
Reactive Power ◽  
Energy System ◽  
Conventional Technique ◽  
Superior Performance ◽  
Power Electronic ◽  
Fuzzy Logic Technique

Grid connected Wind energy conversion system uses power Electronic converters hardly in fixed speed systems except for reactive power compensation. This Power Electronic converter causes major electrical losses and affects power quality of the system. The quality of the voltage and current is also affected by sensitive loads which are used widely in most of Automated Industries and Research laboratories. Disturbances in waveforms occurs which results in harmonics. To improve such power quality problem of the system DVR which is based on fuzzy logic technique is introduced. The system is tested for conventional technique and also with fuzzy logic. The performance is investigated through MATLAB/SIMULINK software. The simulation results confirm the superior performance of the proposed DVR based fuzzy logic technique than conventional technique. The proposed system reduces harmonics as well as mitigates voltage sag/swell.

A Cotton Disease Diagnosis Method Using a Combined Algorithm of Case-Based Reasoning and Fuzzy Logic

2020 ◽  
Author(s):  
Yuhong Dong ◽  
Zetian Fu ◽  
Stevan Stankovski ◽  
Yaoqi Peng ◽  
Xinxing Li
Keyword(s):  
Fuzzy Logic ◽  
Disease Diagnosis ◽  
Case Based Reasoning ◽  
Cotton Production ◽  
Scoring Method ◽  
Disease Symptoms ◽  
Diagnosis Method ◽  
And Control ◽  
Combined Algorithm ◽  
Case Based

Abstract In this study, a cotton disease diagnosis method that uses a combined algorithm of case-based reasoning (CBR) and fuzzy logic was designed and implemented. It focuses on the prevention, diagnosis and control of diseases affecting cotton production in China. Conventional methods of disease diagnosis are primarily based on CBR with reference to user-provided symptoms; however, in most cases, user-provided symptoms do not fully meet the requirements of CBR. To address this problem, fuzzy logic is incorporated into CBR to allow for more flexible and accurate models. With the help of CBR and fuzzy reasoning, three diagnostic results can be obtained by the cotton disease diagnosis system (CDDS) constructed in this study: success, success but not exact and failure. To verify the reliability of the CDDS and its ability to diagnose cotton diseases, its diagnostic accuracy and stability were analyzed and compared with the results obtained by the traditional expert scoring method. The analysis results reveal that the CDDS can achieve a high diagnostic success rate (above 90%) and better diagnostic stability than the traditional expert scoring method when at least four disease symptoms are input. The CDDS provides an independent and objective source of information to assist farmers in the diagnosis and prevention of cotton diseases.

Intelligent Tool for Decision Making Associated With Hospitalization and Sandstorms for the Optimization of Ambulances

2019 ◽  
pp. 50-61
Author(s):  
Estrella D. Molina-Herrera ◽  
Luis Ernesto Cervera-Gómez ◽  
Carlos Herrera
Keyword(s):  
United States ◽  
Decision Making ◽  
El Paso ◽  
Future Research ◽  
Case Based Reasoning ◽  
Dijkstra Algorithm ◽  
Postgraduate Students ◽  
Innovative Model ◽  
Case Based

The shortest path problem is a typical problem of optimization. This chapter presents an innovative model associated with the use of case-based reasoning to solve a problem of routing vehicles in a Hospital of El Paso, United States. In this chapter, diverse components are described to characterize this problem through the use of a knowledge system. The algorithm was developed in Java, thus obtaining a tool which determines the best tracks to the vehicles associated with ambulances. An experiment was realized to probe the validations; the results were used to compare it with the Dijkstra algorithm and determine the quality of the results. The future research of this intelligent tool is to determine an innovative perspective related to episodic knowledge applied to resolution of diverse ambulances, and as this topic is determinative to find and remember the best solutions quickly, additionally the authors compare it with a code from other postgraduate students trying to implement an algorithm similar to logistics but using a shuffled frog leap algorithm.

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